Migration motif: a spatial - temporal pattern mining approach for financial markets

A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio space. Given the financial events of 2008, this first attempt to disentangle the relationships between migration behavior and stock returns is especially timely. Their work, however, derives results only for market segments, not individual companies, and only for one-year moves. Thus, we see a new challenge for financial data mining: how to capture and categorize the migration of individual companies, and how such behavior affects their returns. We propose a novel data mining approach to study the multi-year movement of individual companies. Specifically, we address the question: "How does one discover frequent migration patterns in the stock market?" We present a new trajectory mining algorithm to discover migration motifs in financial markets. Novel features of this algorithm are its handling of a...

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee, John H. Thornton Jr.
• Keywords: Data Mining, Discover Frequent Migration, Financial Data Mining, KDD 2009, Migration Motifs